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LLM-powered chatbots are becoming widely adopted in applications such as healthcare, personal assistants, industry hiring decisions, etc.
Analyzing privacy loss in updates of natural language models
Shruti Tople, Marc Brockschmidt, Boris Köpf, Olga Ohrimenko, and Santiago Zanella Béguelin. 2019 · 1912
Earlier work this paper cites.
The Health Insurance Portability and Accountability Act of 1996 (HIPAA)
Centers for Medicare & Medicaid Services. 1996 · 1996
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Is your chatbot GDPR compliant? open issues in agent design
Rahime Belen Saglam and Jason R. C. Nurse. 2020 · 2005
Earlier work this paper cites.
De-identification of patient notes with recurrent neural networks
Franck Dernoncourt, Ji Young Lee, Ozlem Uzuner, and Peter Szolovits. 2016 · 2016
Earlier work this paper cites.
Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (Text with EEA relevance)
European Commission. 2016 · 2016
Earlier work this paper cites.
Structured prediction models for rnn based sequence labeling in clinical text
Abhyuday N Jagannatha and Hong Yu. 2016 · 2016
Earlier work this paper cites.
Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark. 2016 · 2016
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al. 2018 · 2018
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Earlier work this paper cites.
Privacy risks of general-purpose language models
Xudong Pan, Mi Zhang, Shouling Ji, and Min Yang. 2020 · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
Earlier work this paper cites.
olmpics-on what language model pre-training captures
Alon Talmor, Yanai Elazar, Yoav Goldberg, and Jonathan Berant. 2020 · 2020
Cited alongside, same era.
Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard Hovy, Thang Luong, and Quoc Le. 2020 · 2020
Cited alongside, same era.
Benchmarking differential privacy and federated learning for bert models
Priya Basu, Tiasa Singha Roy, Rakshit Naidu, Zumrut Muftuoglu, Sahib Singh, and Fatemehsadat Mireshghallah. 2021 · 2021
Cited alongside, same era.
NLP is not enough - contextualization of user input in chatbots
Nathan Dolbir, Triyasha Ghosh Dastidar, and Kaushik Roy. 2021 · 2021
Cited alongside, same era.
Does bert pretrained on clinical notes reveal sensitive data?
Eric Lehman, Sarthak Jain, Karl Pichotta, Yoav Goldberg, and Byron C. Wallace. 2021 · 2021
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung. 2023 · 2023
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Quantifying memorization across neural language models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang. 2023 · 2023
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The moral authority of chatgpt
Sebastian Krügel, Andreas Ostermaier, and Matthias Uhl. 2023 · 2023
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Analyzing leakage of personally identifiable information in language models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, and Santiago Zanella-Béguelin. 2023 · 2023
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Cited alongside, same era.
The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
Cited alongside, same era.
Privacy regularization: Joint privacy-utility optimization in language models
Fatemehsadat Mireshghallah, Huseyin A Inan, Marcello Hasegawa, Victor Rühle, Taylor Berg-Kirkpatrick, and Robert Sim. 2021 · 2021
Cited alongside, same era.
Towards improving adversarial training of nlp models
Jin Yong Yoo and Yanjun Qi. 2021 · 2021
Cited alongside, same era.
What does it mean for a language model to preserve privacy?
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, and Florian Tramèr. 2022 · 2022
Cited alongside, same era.
Combing for credentials: Active pattern extraction from smart reply
Bargav Jayaraman, Esha Ghosh, Melissa Chase, Sambuddha Roy, Huseyin Inan, Wei Dai, and David Evans. 2022 · 2022
Cited alongside, same era.
LlamaIndex
Jerry Liu. 2022 · 2022
Cited alongside, same era.
Quantifying privacy risks of masked language models using membership inference attacks
Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick, and Reza Shokri. 2022 · 2022
Cited alongside, same era.
Samsung bans chatgpt, ai chatbots after data leak blunder
Cecily Mauran. 2023 · 2023
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Differentially private in-context learning
Ashwinee Panda, Tong Wu, Jiachen T Wang, and Prateek Mittal. 2023 · 2023
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Collaborating with chatgpt: Considering the implications of generative artificial intelligence for journalism and media education
John V. Pavlik. 2023 · 2023
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The artificially intelligent entrepreneur: Chatgpt, prompt engineering, and entrepreneurial rhetoric creation
Cole E. Short and Jeremy C. Short. 2023 · 2023
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How to keep text private? a systematic review of deep learning methods for privacy-preserving natural language processing
Samuel Sousa and Roman Kern. 2023 · 2023
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"what can chatgpt do" analyzing early reactions to the innovative ai chatbot on twitter
Viriya Taecharungroj. 2023 · 2023
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Ethical chatgpt: Concerns, challenges, and commandments
Jianlong Zhou, Heimo Müller, Andreas Holzinger, and Fang Chen. 2023 · 2023
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Lingxuan Zhu, Weiming Mou, and Rui Chen. 2023 · 2023
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